Probabilistic Methods for Ceramic Component Design and Implications for Standards

Cuccio, J. C.; Peralta, Alonso; Song, Jing-Sheng; Brehm, Peggy J.; Johnson, Curtis A.; Tucker, William T.; Fang, Huacan

doi:10.1520/stp12789s

Cited by 7 publications

(7 citation statements)

References 6 publications

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“…A very important condition for the use of any probabilistic method is that the experimental sample adequately represents the whole population. The situation can be very dangerous if the population is not homogeneous, for example if several kinds of flaws and other defects can be responsible for the strength of a brittle material [11]. All characteristic kinds of defects must be present in the experimental sample (including the largest but rare ones), otherwise the predicted values of low probability strength can be wrong despite the determination of their confidence limits.…”

Section: Discussionmentioning

confidence: 99%

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Reliability Assessment with a Small Amount of Data

Menčík¹

2016

Concise Reliability for Engineers

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Section: Discussionmentioning

confidence: 99%

“…The intervals (11) for all y(x) form a tolerance band around the regression line (9). The tolerance limits for the actual number of cycles (or time) to failure can be obtained using the inverse transformations S = 10 x , N = 10 y , A = 10 a , and m = -b.…”

Section: Linearly Correlated Datamentioning

confidence: 99%

Reliability Assessment with a Small Amount of Data

Menčík¹

2016

Concise Reliability for Engineers

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“…For fast fracture failure modes, stress scale factors depend exclusively on stress gradients and multiaxiallity of the stress field. The factors can be used to predict reliability of a specimen or component, given the peak stress and Weibull parameters as shown in Equation [1].…”

Section: Figure 10 Conventional Fatigue Data Analysis Is Not Capablementioning

confidence: 99%

Status of the CERAMIC/ERICA Probabilistic Life Prediction Codes Development for Structural Ceramic Applications

Schenk¹,

Brehm²,

Menon³

et al. 1999

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation;

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Statistical methods for design of ceramic components for fast fracture and time-dependent failure modes have been advanced to significantly enhance component reliability and reduce baseline data generation costs. The statistical methods are incorporated in AlliedSignal Engines CERAMIC and ERICA computer codes. Use of the codes facilitates generation of material strength and fatigue parameters by pooling data from specimens that are of varying sizes, stressed by dissimilar loading conditions, or tested at a variety of temperatures, and by including specimens that have been proof tested. The codes include approaches to calculate confidence bounds for Weibull and fatigue parameters of censored data as well as for predicted reliability of ceramic components. Rather than presenting highly detailed, previously published theoretical derivations (Cuccio, et al., 1994, Schenk, et al., 1998, Schenk, et al., 1999), this paper presents a summary of general methodology and a synopsis of code features and capabilities. The work was sponsored by the Department of Energy/Oak Ridge National Laboratory (DoE/ORNL) under Contract DE-AC05-84OR21400.

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“…The multiaxial setup was first presented by Batdorf and Heinisch (1978) and Lamon and Evans (1983). This approach has been strengthened and generalized by Cuccio, et. al.…”

Section: Transformation Of Strength Due To Slow Crack Growthmentioning

confidence: 99%

A New Probabilistic Approach for Accurate Fatigue Data Analysis of Ceramic Materials

Schenk¹,

Brehm²,

Menon³

et al. 1999

Volume 4: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation;

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Statistical methods for the design of ceramic components for time-dependent failure modes have been developed which can significantly enhance component reliability, reduce baseline data generation costs, and lead to more accurate estimates of slow crack growth (SCG) parameters. These methods are incorporated into the AlliedSignal Engines CERAMIC and ERICA computer codes. Use of the codes facilitates generation of material strength parameters and SCG parameters simultaneously, by pooling fast fracture data from specimens that are of different sizes, or stressed by different loading conditions, with data derived from static fatigue experiments. The codes also include approaches to calculation of confidence bounds for the Weibull and SCG parameters of censored data and for the predicted reliability of ceramic components. This paper presents a summary of this new fatigue data analysis technique and an example demonstrating the capabilities of the codes with respect to time-dependent failure modes. This work was sponsored by the U.S. Department of Energy Oak Ridge National Laboratory (DoE/ORNL) under Contract No. DE-AC05-84OR21400.

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Probabilistic Methods for Ceramic Component Design and Implications for Standards

Cited by 7 publications

References 6 publications

Reliability Assessment with a Small Amount of Data

Reliability Assessment with a Small Amount of Data

Status of the CERAMIC/ERICA Probabilistic Life Prediction Codes Development for Structural Ceramic Applications

A New Probabilistic Approach for Accurate Fatigue Data Analysis of Ceramic Materials

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